Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks

doi:1005-8885 (2007) 02-0051-07

中国邮电高校学报(英文) ›› 2007, Vol. 14 ›› Issue (2): 51-57.doi: 1005-8885 (2007) 02-0051-07

Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks

王清华;赵保华

University of Science and Technology of China

收稿日期:2006-10-13 修回日期:1900-01-01 出版日期:2007-06-30

Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks

WANG Qing-hua;QU Yu-gui; LIN Zhi-ting;BAI Rong-gang;ZHAO Bao-hua; PAN Quan-ke

University of Science and Technology of China

Received:2006-10-13 Revised:1900-01-01 Online:2007-06-30

摘要/Abstract

摘要：

Wireless sensor networks (WSN) using cooperative multiple-input multiple-output (MIMO) communication are effective tools to collect data in several environments. However, how to apply cooperative MIMO in WSN remains a critical challenge, especially in sparse WSN. In this article, a novel clustering scheme is proposed for the application of cooperative MIMO in sparse WSN by extending the traditional low-energy adaptive clustering hierarchy (LEACH) protocol. This clustering scheme solves the problem that the cluster heads (CH) cannot find enough secondary cluster heads (SCH), which are used to cooperate and inform multiple-antenna transmitters with CHs. On the basis of this protocol, the overall energy consumption of the networks model is developed, and the optimal number of CHs is obtained. The simulation results show that this protocol is feasible for the sparse WSN. The simulation results also illustrate that this protocol provides significant energy efficiencies, even after allowing for additional overheads.

关键词:

MIMO; energy efficiency; cluster head (CH); secondary cluster head (SCH);LEACH

Abstract:

Key words:

MIMO; energy efficiency; cluster head (CH); secondary cluster head (SCH);LEACH

WANG Qing-hua;QU Yu-gui; LIN Zhi-ting;BAI Rong-gang;ZHAO Bao-hua; PAN Quan-ke. Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks[J]. Acta Metallurgica Sinica(English letters), 2007, 14(2): 51-57.

参考文献

1. Ma Shu-hui, Ji Hong, Yue Guang-xin. An energy-aware geographical forwarding protocol utilizing adaptive sleeping in wireless sensor networks. The Journal of China Universities of Posts and Telecommunications, 2006, 13 (1): 15-19

2. Alamouti S M. A simple transmit diversity technique for wireless communications. IEEE Journal on Selected Areas in Communications, 1998, 16 (8): 1451-1458

3. Cui Shu-guang, Goldsmith A J, Bahai A. Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks. IEEE Journal on Selected Areas of Communications, 2004, 22 (6): 1089-1098

4. Zhang Yan-bing, Dai Huai-yu. Selecting optimal transmission strategies for cooperative sensor networks. Proceedings of Conference on information Sciences and systems, March 16-18, 2005, Baltimore, MD, USA. 2005: 335-441

5. Li Xiao-hua, Chen Mo, Liu Wen-yu. Application of STBC-encoded cooperative transmissions in wireless sensor networks. IEEE Signal Processing. Letters., 2005, 12 (2): 134-137

6. Jayaweera S K. An energy-efficient virtual MIMO communications architecture based on V-blast processing for distributed wireless sensor networks. Proceedings of the 1st IEEE Communications Society Conference on Sensor and Ad-hoc Communications and Networks, Oct 4-7, 2004, Santa Clara, CA, USA. New York, NY, USA: IEEE, 2004S: 299-308

7. Li Xiao-hua, Chen Mo, Liu Wen-yu. Cooperative transmissions in wireless sensor networks with imperfect synchronization. IEEE Signal Process Letters , 2004, 11(12): 948-951

8. Abbosh A M, Thiel D. Performance of MIMO-based wireless sensor networks with cochannel interference. Proceedings of Intelligent Sensors, Sensor Networks and Information Processing Conference, Dec 5-8, 2005, Melbourne, Australia, USA: IEEE, 2005: 115-119

9. Heinzelman W, Chandrakasan A, Balakrishnan H. Energy- efficient communication protocol for wireless microsensor networks. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (HICSS), Jan 4-7, 2000, Maui, HI USA. Piscataway, NJ, USA: IEEE Computer Society, 2000: 3005-3014

10. Heinzelman W R, Chandrakasan A P, Balakrishnan H. An application-specific protocol architecture for wireless Communications, microsensor networks. IEEE Transactions on Wireless 2002, 1(4): 660-670

11. Pillutla L S, Krishnamurthy W. Joint rate and cluster optimization cooperative MIMO sensor networks. Proceedings of Signal Processing Advances in Wireless Communications (SPAWC’05),Jun 5-8, 2005, New York, NY, USA. Piscataway, NJ, USA: IEEE, 2005: 265-269

12. Chen Wen-qing, Yuan Yong, Xu Chang-chun, et al. Virtual MIMO protocol based on clustering for wireless sensor network. Proceedings of IEEE Symposium on Computers and Communications (ISCC’05), Jun 27-30, 2005, Murcia, Spain. Piscataway, NJ, USA: IEEE, 2005: 335-340

13. Tong Lang, Zhao Qing, Adireddy S. Sensor networks with mobile agents. Proceedings of Military Communications Conference (MILCOM’03), Oct 13-16, 2003, Monterey, CA, USA.Piscataway, NJ, USA: IEEE, 2003: 688-693

[1]	Wang Qiang, Zhang Yijia, Zhang Tianjiao, Zhang Wenqi, Gao Yue, Tafazolli Rahim. Secure degrees of freedom for general MIMO interference channel under rank-deficiency [J]. 中国邮电高校学报(英文版), 2023, 30(3): 65-77.
[2]	路畅方园邱玲梁晓雯. Performance analysis and low complexity receiver design for extra-large scale MIMO systems with residual hardware impairments[J]. 中国邮电高校学报(英文版), 2023, 30(2): 18-25.
[3]	蔡兴蔚季伟邱玲梁晓雯. Channel puncturing based low-complexity belief propagation detection for multi-user MIMO systems [J]. 中国邮电高校学报(英文版), 2020, 27(6): 8-16.
[4]	张燕航. Surveys on the intelligent surface: an innovative technology for wireless networks beyond 5G [J]. 中国邮电高校学报(英文版), 2020, 27(6): 17-29.
[5]	刘旭谢洋. Channel estimation for multi-panel millimeter wave MIMO based on joint compressed sensing [J]. 中国邮电高校学报(英文版), 2020, 27(6): 1-7.
[6]	郑霖, 汪震, 陈建梅, 林梦莹, 邓小芳. MIMO-FSK non-coherent detection with spatial multiplexing in fast-fading environment[J]. 中国邮电高校学报(英文版), 2020, 27(5): 47-54.
[7]	李新民, 李国民, 刘洋, 郭甜, 李璞. Low-complexity transmit antenna selection algorithm for massive MIMO[J]. 中国邮电高校学报(英文版), 2020, 27(5): 63-68.
[8]	李亚张丹青田心记 . Power allocation scheme for maximizing spectrum efficiency and energy efficiency tradeoff for multi-cluster NOMA system[J]. 中国邮电高校学报(英文版), 2020, 27(3): 62-72.
[9]	梁晓林曹旺斌. Broadband hybrid model for relay-aided cooperative MIMO power line communication systems[J]. 中国邮电高校学报(英文版), 2020, 27(1): 72-80.
[10]	张凯尹长川 Xu Guixian 刘丹谱. Robust hybrid beamforming design for millimeter-wave massive MIMO systems[J]. 中国邮电高校学报(英文版), 2019, 26(3): 44-49.
[11]	Li Bo, Sun Xuehong, Li Chunshu, Xue Kaiping, Zhang Xiaoguang. Downlink energy efficiency modeling and optimization with backhaul awareness and interference price in ultra cellular HetNet[J]. 中国邮电高校学报(英文版), 2019, 26(2): 67-81.
[12]	Qu Tuosi, Cao Haiyan, Xu Fangmin, Wang Xiumin. Low complexity detection algorithm based on optimized Neumann series for massive MIMO system[J]. 中国邮电高校学报(英文版), 2018, 25(6): 97-100.
[13]	郑喆田磊张建华. Elevation spatial characteristic investigation based on 3D massive MIMO channel measurements at 6 GHz[J]. 中国邮电高校学报(英文版), 2018, 25(3): 1-7.
[14]	谢坤黄小红马懋德张沛. Power savings in software defined data center networks via modified hybrid genetic algorithm[J]. 中国邮电高校学报(英文版), 2017, 24(4): 76-86.
[15]	Wang Weimin, Li Muyuan, Liu Yuan’an, Wu Yongle, Li Shulan. Novel physical probe configurations in a multi-probe based 3D MIMO OTA setup[J]. 中国邮电高校学报(英文版), 2017, 24(1): 60-66.

Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks

Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价